Home // International Journal On Advances in Intelligent Systems, volume 15, numbers 1 and 2, 2022 // View article
Authors:
Masayuki Ando
Yoshinobu Kawahara
Wataru Sunayama
Yuji Hatanaka
Keywords: interpretation support; deep learning; text mining; text classification; data visualization
Abstract:
We developed an interpretation support system for classification patterns extracted from deep learning with texts using a hidden Markov model (HMM) and verified its effectiveness. It is well known that classification patterns by using deep learning models are often difficult to interpret the reasons derived. In the proposed system, the content of deep learning results is extracted using structure of HMM, and classification patterns are provided for the system users to interpret the learned features. The system then displays learned network structures so that anyone can easily understand the learning results. In verification experiments to confirm the effectiveness of the system, based on the learning result of deep learning classifying sentences, participants were divided into two groups. One group used the proposed system, while the other group used a system that displays words with high Term Frequency-Inverse Document Frequency (TFIDF) values. Both groups were instructed to give meanings of classification patterns peculiar to each output. The results indicate that the participants who used the proposed system were able to understand the meanings of the classification patterns of deep learning with texts better than those who used the comparison system.
Pages: 24 to 34
Copyright: Copyright (c) to authors, 2022. Used with permission.
Publication date: June 30, 2022
Published in: journal
ISSN: 1942-2679